基于小波分解和灰度共生矩阵的纹理图像检索

Texture Image Retrival Based on Wavelet Decomposition and Gray Level Co-occurrence Matrix

采用Daubechies4小波对图像进行三层Mallat塔式分解,取每个分解层次上的每个子带图像的能量,加入在低频子带上提取的灰度共生矩阵统计量,来形成最终的特征向量以提高检索精度。

Texture likelihood research is an important part of the content-based image retrieval research. Adoptes wavelet Daubechies4 to conduct a three level Mallat pyramid decomposition, takes the energy of each subband image in each decomposition level and adds in the gray level co-occurrence matrix statistics extracted in the low-frequency subband to become the final feature vector in order to increase the retrieval accuracy.